Mapping of Submerged Aquatic Vegetation in Rivers From Very High Resolution Image Data, Using Object Based Image Analysis Combined with Expert Knowledge

The use of remote sensing for monitoring of submerged aquatic vegetation (SAV) in fluvial environments has been limited by the spatial and spectral resolution of available image data. The absorption of light in water also complicates the use of common image analysis methods. This paper presents the results of a study that uses very high resolution (VHR) image data, collected with a Near Infrared sensitive DSLR camera, to map the distribution of SAV species for three sites along the Desselse Nete, a lowland river in Flanders, Belgium. Plant species, including Ranunculus aquatilis L., Callitriche obtusangula Le Gall, Potamogeton natans L., Sparganium emersum L. and Potamogeton crispus L., were classified from the data using Object-Based Image Analysis (OBIA) and expert knowledge. A classification rule set based on a combination of both spectral and structural image variation (e.g. texture and shape) was developed for images from two sites. A comparison of the classifications with manually delineated ground truth maps resulted for both sites in 61% overall accuracy. Application of the rule set to a third validation image, resulted in 53% overall accuracy. These consistent results show promise for species level mapping in such biodiverse environments, but also prompt a discussion on assessment of classification accuracy.

Detecting Submerged Macrophytes in a UK Chalk Stream Using Field Spectroscopy

Various studies using optical remote sensing in the marine environment have shown the possibilities of spectral discrimination of benthic macro and micro-algae. For in-land water bodies only very recently studies of have explored similar use of optical remote sensing to identify the taxonomic composition of algae and rooted plant communities. The importance of these communities for the functioning of river ecosystems warrants further research. In the study presented here, field spectroscopy is used to assess the possibilities of optically detecting macrophytes in a UK chalk streams. Spectral signatures of four common macrophytes were measured using a hand-held GER1500 spectroradiometer. Despite the strong absorption of near infrared in water, the results show that information on NIR can clearly contribute to the detection of submerged vegetation in shallow UK chalk stream environments. Observed spectra compare well with simulated submerged vegetation spectra, based on water absorption coefficients only. The field investigations, which were performed in the river Wylye, also indicate the confounding effects of specular reflection from riparian vegetation. The results of this study can inform remote sensing studies of the riverine environment using multi-spectral/low altitude sensors. Such larger scale studies will be highly beneficial for monitoring variation in chalk stream bioindicators, such as ranunculus.

Quantifying Submerged Fluvial Topography Using Hyperspatial Resolution UAS Imagery and Structure From Motion Photogrammetry.

Quantifying the topography of rivers and their associated bedforms has been a fundamental concern of fluvial geomorphology for decades. Such data, acquired at high temporal and spatial resolutions, are increasingly in demand for process-oriented investigations of flow hydraulics, sediment dynamics and in-stream habitat. In these riverine environments, the most challenging region for topographic measurement is the wetted, submerged channel. Generally, dry bed topography and submerged bathymetry are measured using different methods and technology. This adds to the costs, logistical challenges and data processing requirements of comprehensive river surveys. However, some technologies are capable of measuring the submerged topography. Through-water photogrammetry and bathymetric LiDAR are capable of reasonably accurate measurements of channel beds in clear water. Whilst the cost of bathymetric LiDAR remains high and its resolution relatively coarse, the recent developments in photogrammetry using Structure from Motion (SfM) algorithms promise a fundamental shift in the accessibility of topographic data for a wide range of settings. Here we present results demonstrating the potential of so called SfM-photogrammetry for quantifying both exposed and submerged fluvial topography at the mesohabitat scale. We show that imagery acquired from a rotary-winged Unmanned Aerial System (UAS) can be processed in order to produce digital elevation models (DEMs) with hyperspatial resolutions (c. 0.02 m) for two different river systems over channel lengths of 50-100 m. Errors in submerged areas range from 0.016 m to 0.089 m, which can be reduced to between 0.008 m and 0.053 m with the application of a simple refraction correction. This work therefore demonstrates the potential of UAS platforms and SfM-photogrammetry as a single technique for surveying fluvial topography at the mesoscale (defined as lengths of channel from c.10 m to a few hundred metres). This article is protected by copyright. All rights reserved.

Urban Ponds as an Aquatic Biodiversity Resource in Modified Landscapes

Urbanization is a global process contributing to the loss and fragmentation of natural habitats. Many studies have focused on the biological response of terrestrial taxa and habitats to urbanization. However, little is known regarding the consequences of urbanization on freshwater habitats, especially small lentic systems. In this study we examined aquatic macroinvertebrate diversity (family and species level) and variation in community composition between 240 urban and 782 non-urban ponds distributed across the UK. Contrary to predictions, urban ponds supported similar numbers of invertebrate species and families compared to non-urban ponds. Similar gamma diversity was found between the two groups at both family and species taxonomic levels. The biological communities of urban ponds were markedly different to those of non-urban ponds and the variability in urban pond community composition was greater than that in non-urban ponds, contrary to previous work showing homogenisation of communities in urban areas. Positive spatial autocorrelation was recorded for urban and non-urban ponds at 0-50 km (distance between pond study sites) and negative spatial autocorrelation was observed at 100-150 km, and was stronger in urban ponds in both cases. Ponds do not follow the same ecological patterns as terrestrial and lotic habitats (reduced taxonomic richness) in urban environments; in contrast they support high taxonomic richness and contribute significantly to regional faunal diversity. Individual cities are complex structural mosaics which evolve over long periods of time and are managed in diverse ways, promoting the development of a wide-range of environmental conditions and habitat niches in urban ponds which can promote greater heterogeneity between pond communities at larger scales. Ponds provide an opportunity for managers and environmental regulators to conserve and enhance freshwater biodiversity in urbanized landscapes whilst also facilitating key ecosystem services including storm water storage and water treatment.